https://irjet.net/archives/V4/i7/IRJET-V4I7613.pdf

1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 4 Issue: 7 | July 2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 3039
IMPLEMENTATION OF SMART HELMET
Deekshitha K J1, Pushpalatha S2
1Student, DECS dept, VTU PG CENTER MYSURU, Karnataka, India
2Assistant professor, DECS dept, VTU PG CENTER MYSURU, Karnataka, India
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Abstract - There was a survey till 31 Mar 2015, Which clear
tells that there are total of 154.3 million two wheelers are
there in India, considering only the registered and renewed
vehicle in to consideration, as the density of the two wheelers
increases, there the main risk factor is to provide the safety to
the riders.70% of the accidents reported are subjected to two
wheelers and out 3 accidents in India 2accidents involve two
wheelers as a victims, accidents of twowheelersarebecauseof
high density roads, heavy traffic, rash or negligence driving,
drunk & Drive and a Sleepy riding, many times even after the
accidents, accidents will not be reported properly or even the
medical aid or assistance will not be available to the riders
because of poor or no communication of the accidents, which
leads to many number of the death in the recent years.
In this paper we are developinganIoTproductcalled
Smart helmet, which comprises of to units, motor unit and
helmet unit, Helmet unit consists of the alcohol and Eye blink
sensor, Alcohol Sensor will not allow rider totakeonbikeafter
drinking alcohol and eye blink sensor raises the alarm in
sleeping conditions. Motor unit is able to communicate with
the care takers with messages and GPS helps the system to
track the location of the bike in case of the accidents, also this
system act as accident prevention and detection system.
Keywords: Smart Helmet, IoT, GSM, GPS, Sensors,
Accidents, Smart Helmet, Prevention
I. INTRODUCTION
The monitoring of physiological signals using
wearable devices is increasingly becominga prerequisitefor
the assessment of the state of body and mind in natural
environments. This has been facilitated by small-scale
analogue and digital integrated circuit technology, together
with on-chip processing power for dealing with movement
induced artifacts in bio potentials, which are present when
performing daily activities. Physiological signalsrecorded in
real life tend to be notoriously weak andwitha lowsignal to-
noise ratio (SNR). To this end, an amplifier with a high
common mode rejection ratio is required; such high quality
bio-appliers are typically integrated into the analogue front
end of large stationary devices. Because of the many leads
and electrodes required, such devices are well suited for
clinical environments, where patients are normally
stationary (except e.g. for cardiac stress tests), so that the
noise level is relatively low.
Objectives
Objective of this Project is to design an intelligent or
smart helmet, which act as a Security system and also a
monitoring system for the two wheeler and its rider, This
embedded system is consists of the Sensors network with
Communication modules, which helps to stop the drive or
not to allow the driving at the critical orabnormal situations,
also we are intended to set the accident detection system.
II. LITERATURE SURVEY
Smart Helmet with Sensors for Accident [1] The impact
when a motorcyclist involves in a high speed accident
without wearing a helmet is very dangerous and can cause
fatality. Wearing a helmet can reduce shock from the impact
and may save a life. There are many countries enforcing a
regulation that requires the motorcycle’s rider to wear a
helmet when riding on their motorcycle, Malaysia is an
example. With this reason, this projectisspeciallydeveloped
as to improve the safety of the motorcycle’s rider.
Motorcyclist will be alarmed when the speed limit is
exceeded. A Force Sensing Resistor (FSR) and BLDC Fan are
used for detection of the rider’s head and detection of
motorcycle’s speed respectively. A 315 MHz Radio
Frequency Module as wireless link which able to
communicate between transmitter circuit and receiver
circuit. PIC16F84a is a microcontroller to control the entire
component in the system. Only when the rider buckled the
helmet then only the motorcycle’s engine will start. A LED
will flash if the motor speed exceeds 100 km/hour.
Keywords-Microcontroller PIC16F844a, 315 MHz Radio
Frequency Module, Force Sensing Resistance, BLDC Fan,
5VRelay, LM311 and IC 555.
Smart Helmets for Automatic Control of Headlamps
[2] Intelligent Safety Helmet for Motorcyclist is a project
undertaken to increase the rate of road safety among
motorcyclists. There are many countries enforcing
regulations to wear a helmet while riding. India is an
example. The idea is obtained after knowing that the
increasing number of fatal road accidents over the years is
cause for concern among motorcyclists. This project is
designed to introduce automatic autonomous headlight
technology for the safety of motorcyclist. Here, we focus on
intelligent headlamps that react according to the rider’s
facial movement. It makes use of accelerometer and other

2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 4 Issue: 7 | July 2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 3040
sensors to direct small electric motors built into the
headlight casing to turn the headlights accordingly.
Keywords- Smart helmets, Headlamps, Accelerometer, RF
transmitter, RF receiver, Servo motor
A Smart Safety Helmet using IMU and EEG sensors
for worker fatigue detection[3] It isknownthatheadgesture
and brain activity can reflect some human behaviors related
to a risk of accident when using machine-tools. Theresearch
presented in this paper aims at reducing the risk of injury
and thus increase worker safety. Instead of using camera,
this paper presents a Smart Safety Helmet (SSH) in order to
track the head gestures and the brain activity of the worker
to recognize anomalous behavior. Information extracted
from SSH is used for computing risk of an accident (a safety
level) for preventing and reducing injuries or accidents. The
SSH system is an inexpensive, non-intrusive, noninvasive,
and non-vision based system, which consists of an Inertial
Measurement Unit (IMU) and dry EEG electrodes. Adaptec
device, such as vibrotactile motor,isintegratedtothehelmet
in order to alert the operator when computed risk level
reaches a threshold. Once the risk level of accident breaks
the threshold, a signal will be sent wirelessly to stop the
relevant machine tool or process.
Key words — Safety; Head motion recognition; IMU; EEG;
accident avoidance; human machine interaction
III. METHODOLOGY
This modulecontainsdifferentsensorsanda transmitter
Circuitry. Microcontroller contains three sensors which are
alcohol sensor, vibrate sensor and IR sensor. Alcohol sensor
has been utilized to recognize the alcohol focus. The alcohol
sensor will be put close to the mouth of the rider, inside the
helmet. Vibrate sensor is utilized for crash location. Another
microcontroller containstwosensors whicharepulsesensor
and UV sensor. Pulse sensor has been utilized for measuring
of pulse rate. When the pulse rate increases it stimulates
LED1 which blinks white light. UV sensorwill sensethefront
moving vehicle to avoid collision also controlling the
accident. If any vehicle detected near to our vehicle LED2 is
activated which blinks red light. A RF transmitter which can
transmit information from any controller or standard
Encode IC has been utilized. The RF transmitter transmits
information from the microcontroller on the helmet side to
the recipient on the vehicle side through transmit antenna.
Fig.1 Transmitter side block diagram
This module comprises of a LCD, GSM module, RF
recipient, Receive antenna, DC motor, drive L293D and GPS
module. This works with wireless communication. Receive
antenna receives information from the transmit antenna
then sends to the RF receiver whichgetstheinformationand
sends it to the microcontroller for further Handling. In the
coming of an accident, the GPS module will gain the co-
ordinates of the accident site. These co-ordinatesaresent by
means of GSM module to a pre defined number. The person
who belongs to this number receives the detection of
accident along with location with the help of GPS. The start
status is controlled by the microcontroller relying upon
different conditions. Any sensor senses their activity DC
motor decreases speed by using drive called driver L293D.
LCD is used to display the conditions of sensors activities.
Fig.2 Receiver side block diagram

3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 4 Issue: 7 | July 2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 3041
RESULTS
Fig.3 Transmitter side view
This transmitter side of helmet consists of arduino
uno microcontroller, UVsensor,pulsesensor,alcohol sensor.
Arduino uno microcontroller controls the transmitter part
which connects to all sensors. First sensor UV sensor which
measures the distance of the front moving vehicle. It locates
the distance between vehicles, at the time of critical
positions then speed of the vehicle decreases and then it
stops with the help of RF transceiver. Second sensor pulse
sensor which used to measures the pulse rate. Usually
human normal pulse rate 80-120 this sensor measures
continuously but it sends information after crosses normal
pulse rate it seems like person is in trouble. Third sensor
alcohol sensor which utilizes to detect alcohol content this
mainly used for prevent accident. The person is in drunken
condition sends information to receiver that time bike
decreases the speed then come to off state with the help of
RF transceiver.
Fig.4 Transmitter front view
The same transmitter of helmet consists of vibrate sensor
and IR sensor. Fourth sensor vibrate sensor used for detect
the accident at the time of critical sutuation. This sends
information to receiver also sends message to pre difined
number like the person is in trounle.
The fifth sensor used called IR sensor which measures the
drozymness of people. This also sends information to the
receiver decreases the speed of vehicle then come to off
state.
Fig.5 Receiver view
This receiver consists of GPS, GSM, LCD display, DC
motor and L293D driver. The GPS is used for identify the
location of accident. This receives in our cell phone. GSM is
used for messaging and calling purpose when the accident
detect. LCD display shows the output of the all sensors.Ifthe
vibration sensor activates it seems like the person is in
trouble. If the IR sensor activates it seems like the person is
in sleepy and as same if the alcohol sensor activates it seems
like alcohol detected. DC motor is used in receiver part of
vehicle. At the time of sensor activates itdecreasesthespeed
and then going to be stop state. This DC motor run by using
the motor driver called L293D driver. This helps to drive DC
motor.
CONCLUSION
We have conducted a proof-of-concept study to
demonstrate that electrodes mounted to the inside of a
motorcycle helmet can reliably record doziness, alcohol
detection and pulse rate. Recording of pulse rate signals has
been conducted. Helmet can also help topreventthedamage
occurred to the vehicles by the accidents. So this helps in
curbing the road accidents by implementing mandatory
Helmet protection and detection of alcohol content during
the starting on of the bike and most importantly saves the
precious life of a person as one cannot run a motor vehicle
once he is drunk and if the helmet is not present. Family
members will be informed as well. We can detect the safer
distance between the two vehicles by using UV sensor. The
LED is used for sensors activities also buzzer is used for
alarm. By inserting a buzzer in the helmet, the motorcyclist
will be more alert and will slow down the motorcycle once
they received the signal. This system also helps in efficient
handling of the outcome of accidents by sending a SMS with
the location of the biker to the family member. This ensures
that the victims get proper and prompt medical attention, if
met with an accident.

4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 4 Issue: 7 | July 2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 3042
REFERENCES
[1]Smart Helmet with SensorsforAccident PreventionMohd
Khairul Afiq Mohd Rasli, Nina Korlina Madzhi, Juliana Johari
Faculty of Electrical Engineering UniversitiTeknologiMARA
40450 Shah Alam Selangor, MALAYSIA
[2]Smart Helmets for Automatic Control of Headlamps
Muthiah M1, Aswin Natesh V2, Sathiendran R K3
Undergraduate Student, Dept. of Electrical and Electronics
Engineering
[3]A Smart Safety Helmet using IMU and EEG sensors for
worker fatigue detection
Ping Li, Ramy Meziane, Martin J.-D. Otis, Hassan Ezzaidi,
REPARTI Center, University of Quebec at Chicoutimi
Chicoutimi, Canada